Wildfire Behaviour and Danger Ratings

Planas, Eulàlia; Pastor, Elsa

doi:10.1002/9781118529539.ch4

Cited by 4 publications

(2 citation statements)

References 82 publications

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“…In addition, the close spatial proximity of high-severity and low or moderate burnt areas was due to the local topography and weather conditions during the fire. Topographic traits markedly interact with local climate conditions, directly affecting fire propagation [61,67]. These traits, together with the seasonal variation in the moisture content of live [68] and dead fuels [69], and thus their flammability [70,71], had generated a patchwork of mixed-severity wildfires [72,73].…”

Section: Field-based Burn Index Performancementioning

confidence: 99%

Detecting Burn Severity across Mediterranean Forest Types by Coupling Medium-Spatial Resolution Satellite Imagery and Field Data

et al. 2020

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In Mediterranean countries, in the year 2017, extensive surfaces of forests were damaged by wildfires. In the Vesuvius National Park, multiple summer wildfires burned 88% of the Mediterranean forest. This unprecedented event in an environmentally vulnerable area suggests conducting spatial assessment of the mixed-severity fire effects for identifying priority areas and support decision-making in post-fire restoration. The main objective of this study was to compare the ability of the delta Normalized Burn Ratio (dNBR) spectral index obtained from Landsat-8 and Sentinel-2A satellites in retrieving burn severity levels. Burn severity levels experienced by the Mediterranean forest communities were defined by using two quali-quantitative field-based composite burn indices (FBIs), namely the Composite Burn Index (CBI), its geometrically modified version CBI (GeoCBI), and the dNBR derived from the two medium-resolution multispectral remote sensors. The accuracy of the burn severity map produced by using the dNBR thresholds developed by Key and Benson (2006) was first evaluated. We found very low agreement (0.15 < K < 0.21) between the burn severity class obtained from field-based indices (CBI and GeoCBI) and satellite-derived metrics (dNBR) from both Landsat-8 and Sentinel-2A. Therefore, the most appropriate dNBR thresholds were rebuilt by analyzing the relationships between two field-based (CBI and GeoCBI) and dNBR from Landsat-8 and Sentinel-2A. By regressing alternatively FBIs and dNBRs, a slightly stronger relationship between GeoCBI and dNBR metrics obtained from the Sentinel-2A remote sensor (R2 = 0.69) was found. The regressed dNBR thresholds showed moderately high classification accuracy (K = 0.77, OA = 83%) for Sentinel-2A, suggesting the appropriateness of dNBR-Sentinel 2A in assessing mixed-severity Mediterranean wildfires. Our results suggest that there is no single set of dNBR thresholds that are appropriate for all burnt biomes, especially for the low levels of burn severity, as biotic factors could affect satellite observations.

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Section: Field-based Burn Index Performancementioning

confidence: 99%

Detecting Burn Severity across Mediterranean Forest Types by Coupling Medium-Spatial Resolution Satellite Imagery and Field Data

et al. 2020

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“…Meteorological variables (both on the scales of climate and weather), topography, and fuel characteristics influence and determine the propagation of fire and its behaviour. For instance, climatic and meteorological conditions influence the ignition and development of fires (Benson et al 2009) where solar radiation, air temperature and relative humidity affect ignition and propagation of fires (Planas and Pastor, 2013). It is argued that wind has the greatest effect on fire spread and fire intensity through its direct effect on the combustion reaction (Albini, 1982, Beer 1991, Taylor et al 2004, Sullivan and Ball, 2012.…”

Section: List Of Figuresmentioning

confidence: 99%

Spatial wildfire occurrence data for the United States, 1992-2013 [FPA_FOD_20150523] (3rd Edition)

Short¹

Forest Service Research Data Archive

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Data sources and analysis approaches used in this thesis ………....75 3.2.1. Time period analysed in this thesis…………………...………..75 3.2.2. Data sources and formatting of datasets for analysis ……….76 3.2.3. Data processing, statistical analysis, and generation of novel datasets ………………………………………………………………….78 8 Chapter 4: A comparison of the US National Fire Danger Rating System (NFDRS) with recorded fire occurrence and final fire size …………………89 4.1. Introduction ……………………………………………………………….90 4.2. Methods …………………………………………………………………..96 4.2.1. NFDRS fire danger data ………………………………………100 4.2.2. USFS FPA FOD ………………………………………………..103 4.2.3. Plotting and correlation analysis ……………………………...104 4.3. Results …………………………………………………………………..107 4.3.1. Correlation coefficient maps and histograms ……………….107 4.3.2. National scatter plots and summary trends …………………1144.4. Discussion ………………………………………………………………121 4.5. Conclusion ………………………………………………………………127 Chapter 5: How accurate are the NFDRS 1-day forecasts? ………………133 5.1. Introduction ……………………………………………………………...133 5.2. Methods ……………………………………………………………….…137 5.2.1. Data sources and processing …………………………………137 5.2.2. Correlation analysis of Forecasted and Observed NFDRS outputs ………………………………………………………………….140 5.2.3. Correlations of forecasted FDIs vs Fire Activity …………….141 5.3. Results …………………………………………………………………...142 5.3.1. Correlation analysis of Forecasted and Observed NFDRS outputs ………………………………………………………………….142 5.3.2. Heatmaps of Forecasted vs Observed NFDRS outputs …...146 5.3.3. Linear models of Forecasted vs Observed NFDRS Outputs ………………………………………………………………....146 5.3.4. Correlations of forecasted FDIs vs Fire Activity …………….148 5.4. Discussion ……………………………………………………………….154 5.5. Conclusion ………………………………………………………………163 Chapter 6: The impact of US National Fire Danger Rating System (NFDRS)

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Wildland Fires

Simeoni¹

2016

SFPE Handbook of Fire Protection Engineering

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Wildfire Behaviour and Danger Ratings

Cited by 4 publications

References 82 publications

Detecting Burn Severity across Mediterranean Forest Types by Coupling Medium-Spatial Resolution Satellite Imagery and Field Data

Detecting Burn Severity across Mediterranean Forest Types by Coupling Medium-Spatial Resolution Satellite Imagery and Field Data

Spatial wildfire occurrence data for the United States, 1992-2013 [FPA_FOD_20150523] (3rd Edition)

Wildland Fires

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